BOT MAN STRATEGYthis indicator is made and updated by SPXHERO
the daily updates is to add new levels in SPX500 that are aligned with our new innovative strategy to read market movements and define useful Support and resistant
S&P 500 (SPX500)
MACD Forecast Colorful [DiFlip]MACD Forecast Colorful
The Future of Predictive MACD — is one of the most advanced and customizable MACD indicators ever published on TradingView. Built on the classic MACD foundation, this upgraded version integrates statistical forecasting through linear regression to anticipate future movements — not just react to the past.
With a total of 22 fully configurable long and short entry conditions, visual enhancements, and full automation support, this indicator is designed for serious traders seeking an analytical edge.
⯁ Real-Time MACD Forecasting
For the first time, a public MACD script combines the classic structure of MACD with predictive analytics powered by linear regression. Instead of simply responding to current values, this tool projects the MACD line, signal line, and histogram n bars into the future, allowing you to trade with foresight rather than hindsight.
⯁ Fully Customizable
This indicator is built for flexibility. It includes 22 entry conditions, all of which are fully configurable. Each condition can be turned on/off, chained using AND/OR logic, and adapted to your trading model.
Whether you're building a rules-based quant system, automating alerts, or refining discretionary signals, MACD Forecast Colorful gives you full control over how signals are generated, displayed, and triggered.
⯁ With MACD Forecast Colorful, you can:
• Detect MACD crossovers before they happen.
• Anticipate trend reversals with greater precision.
• React earlier than traditional indicators.
• Gain a powerful edge in both discretionary and automated strategies.
• This isn’t just smarter MACD — it’s predictive momentum intelligence.
⯁ Scientifically Powered by Linear Regression
MACD Forecast Colorful is the first public MACD indicator to apply least-squares predictive modeling to MACD behavior — effectively introducing machine learning logic into a time-tested tool.
It uses statistical regression to analyze historical behavior of the MACD and project future trajectories. The result is a forward-shifted MACD forecast that can detect upcoming crossovers and divergences before they appear on the chart.
⯁ Linear Regression: Technical Foundation
Linear regression is a statistical method that models the relationship between a dependent variable (y) and one or more independent variables (x). The basic formula for simple linear regression is:
y = β₀ + β₁x + ε
Where:
y = predicted variable (e.g., future MACD value)
x = independent variable (e.g., bar index)
β₀ = intercept
β₁ = slope
ε = random error (residual)
The regression model calculates β₀ and β₁ using the least squares method, minimizing the sum of squared prediction errors to produce the best-fit line through historical values. This line is then extended forward, generating a forecast based on recent price momentum.
⯁ Least Squares Estimation
The regression coefficients are computed with the following formulas:
β₁ = Σ((xᵢ - x̄)(yᵢ - ȳ)) / Σ((xᵢ - x̄)²)
β₀ = ȳ - β₁x̄
Where:
Σ denotes summation; x̄ and ȳ are the means of x and y; and i ranges from 1 to n (number of observations). These equations produce the best linear unbiased estimator under the Gauss–Markov assumptions — constant variance (homoscedasticity) and a linear relationship between variables.
⯁ Regression in Machine Learning
Linear regression is a foundational model in supervised learning. Its ability to provide precise, explainable, and fast forecasts makes it critical in AI systems and quantitative analysis.
Applying linear regression to MACD forecasting is the equivalent of injecting artificial intelligence into one of the most widely used momentum tools in trading.
⯁ Visual Interpretation
Picture the MACD values over time like this:
Time →
MACD →
A regression line is fitted to recent MACD values, then projected forward n periods. The result is a predictive trajectory that can cross over the real MACD or signal line — offering an early-warning system for trend shifts and momentum changes.
The indicator plots both current MACD and forecasted MACD, allowing you to visually compare short-term future behavior against historical movement.
⯁ Scientific Concepts Used
Linear Regression: models the relationship between variables using a straight line.
Least Squares Method: minimizes squared prediction errors for best-fit.
Time-Series Forecasting: projects future data based on past patterns.
Supervised Learning: predictive modeling using labeled inputs.
Statistical Smoothing: filters noise to highlight trends.
⯁ Why This Indicator Is Revolutionary
First open-source MACD with real-time predictive modeling.
Scientifically grounded with linear regression logic.
Automatable through TradingView alerts and bots.
Smart signal generation using forecasted crossovers.
Highly customizable with 22 buy/sell conditions.
Enhanced visuals with background (bgcolor) and area fill (fill) support.
This isn’t just an update — it’s the next evolution of MACD forecasting.
⯁ Example of simple linear regression with one independent variable
This example demonstrates how a basic linear regression works when there is only one independent variable influencing the dependent variable. This type of model is used to identify a direct relationship between two variables.
⯁ In linear regression, observations (red) are considered the result of random deviations (green) from an underlying relationship (blue) between a dependent variable (y) and an independent variable (x)
This concept illustrates that sampled data points rarely align perfectly with the true trend line. Instead, each observed point represents the combination of the true underlying relationship and a random error component.
⯁ Visualizing heteroscedasticity in a scatterplot with 100 random fitted values using Matlab
Heteroscedasticity occurs when the variance of the errors is not constant across the range of fitted values. This visualization highlights how the spread of data can change unpredictably, which is an important factor in evaluating the validity of regression models.
⯁ The datasets in Anscombe’s quartet were designed to have nearly the same linear regression line (as well as nearly identical means, standard deviations, and correlations) but look very different when plotted
This classic example shows that summary statistics alone can be misleading. Even with identical numerical metrics, the datasets display completely different patterns, emphasizing the importance of visual inspection when interpreting a model.
⯁ Result of fitting a set of data points with a quadratic function
This example illustrates how a second-degree polynomial model can better fit certain datasets that do not follow a linear trend. The resulting curve reflects the true shape of the data more accurately than a straight line.
⯁ What is the MACD?
The Moving Average Convergence Divergence (MACD) is a technical analysis indicator developed by Gerald Appel. It measures the relationship between two moving averages of a security’s price to identify changes in momentum, direction, and strength of a trend. The MACD is composed of three components: the MACD line, the signal line, and the histogram.
⯁ How to use the MACD?
The MACD is calculated by subtracting the 26-period Exponential Moving Average (EMA) from the 12-period EMA. A 9-period EMA of the MACD line, called the signal line, is then plotted on top of the MACD line. The MACD histogram represents the difference between the MACD line and the signal line.
Here are the primary signals generated by the MACD:
• Bullish Crossover: When the MACD line crosses above the signal line, indicating a potential buy signal.
• Bearish Crossover: When the MACD line crosses below the signal line, indicating a potential sell signal.
• Divergence: When the price of the security diverges from the MACD, suggesting a potential reversal.
• Overbought/Oversold Conditions: Indicated by the MACD line moving far away from the signal line, though this is less common than in oscillators like the RSI.
⯁ How to use MACD forecast?
The MACD Forecast is built on the same foundation as the classic MACD, but with predictive capabilities.
Step 1 — Spot Predicted Crossovers:
Watch for forecasted bullish or bearish crossovers. These signals anticipate when the MACD line will cross the signal line in the future, letting you prepare trades before the move.
Step 2 — Confirm with Histogram Projection:
Use the projected histogram to validate momentum direction. A rising histogram signals strengthening bullish momentum, while a falling projection points to weakening or bearish conditions.
Step 3 — Combine with Multi-Timeframe Analysis:
Use forecasts across multiple timeframes to confirm signal strength (e.g., a 1h forecast aligned with a 4h forecast).
Step 4 — Set Entry Conditions & Automation:
Customize your buy/sell rules with the 20 forecast-based conditions and enable automation for bots or alerts.
Step 5 — Trade Ahead of the Market:
By preparing for future momentum shifts instead of reacting to the past, you’ll always stay one step ahead of lagging traders.
📈 BUY
🍟 Signal Validity: The signal will remain valid for X bars.
🍟 Signal Sequence: Configurable as AND or OR.
🍟 MACD > Signal Smoothing
🍟 MACD < Signal Smoothing
🍟 Histogram > 0
🍟 Histogram < 0
🍟 Histogram Positive
🍟 Histogram Negative
🍟 MACD > 0
🍟 MACD < 0
🍟 Signal > 0
🍟 Signal < 0
🍟 MACD > Histogram
🍟 MACD < Histogram
🍟 Signal > Histogram
🍟 Signal < Histogram
🍟 MACD (Crossover) Signal
🍟 MACD (Crossunder) Signal
🍟 MACD (Crossover) 0
🍟 MACD (Crossunder) 0
🍟 Signal (Crossover) 0
🍟 Signal (Crossunder) 0
🔮 MACD (Crossover) Signal Forecast
🔮 MACD (Crossunder) Signal Forecast
📉 SELL
🍟 Signal Validity: The signal will remain valid for X bars.
🍟 Signal Sequence: Configurable as AND or OR.
🍟 MACD > Signal Smoothing
🍟 MACD < Signal Smoothing
🍟 Histogram > 0
🍟 Histogram < 0
🍟 Histogram Positive
🍟 Histogram Negative
🍟 MACD > 0
🍟 MACD < 0
🍟 Signal > 0
🍟 Signal < 0
🍟 MACD > Histogram
🍟 MACD < Histogram
🍟 Signal > Histogram
🍟 Signal < Histogram
🍟 MACD (Crossover) Signal
🍟 MACD (Crossunder) Signal
🍟 MACD (Crossover) 0
🍟 MACD (Crossunder) 0
🍟 Signal (Crossover) 0
🍟 Signal (Crossunder) 0
🔮 MACD (Crossover) Signal Forecast
🔮 MACD (Crossunder) Signal Forecast
🤖 Automation
All BUY and SELL conditions can be automated using TradingView alerts. Every configurable condition can trigger alerts suitable for fully automated or semi-automated strategies.
⯁ Unique Features
Linear Regression: (Forecast)
Signal Validity: The signal will remain valid for X bars
Signal Sequence: Configurable as AND/OR
Table of Conditions: BUY/SELL
Conditions Label: BUY/SELL
Plot Labels in the graph above: BUY/SELL
Automate & Monitor Signals/Alerts: BUY/SELL
Background Colors: "bgcolor"
Background Colors: "fill"
Linear Regression (Forecast)
Signal Validity: The signal will remain valid for X bars
Signal Sequence: Configurable as AND/OR
Table of Conditions: BUY/SELL
Conditions Label: BUY/SELL
Plot Labels in the graph above: BUY/SELL
Automate & Monitor Signals/Alerts: BUY/SELL
Background Colors: "bgcolor"
Background Colors: "fill"
ADX Forecast Colorful [DiFlip]ADX Forecast Colorful
Introducing one of the most advanced ADX indicators available — a fully customizable analytical tool that integrates forward-looking forecasting capabilities. ADX Forecast Colorful is a scientific evolution of the classic ADX, designed to anticipate future trend strength using linear regression. Instead of merely reacting to historical data, this indicator projects the future behavior of the ADX, giving traders a strategic edge in trend analysis.
⯁ Real-Time ADX Forecasting
For the first time, a public ADX indicator incorporates linear regression (least squares method) to forecast the future behavior of ADX. This breakthrough approach enables traders to anticipate trend strength changes based on historical momentum. By applying linear regression to the ADX, the indicator plots a projected trendline n periods ahead — helping users make more accurate and timely trading decisions.
⯁ Highly Customizable
The indicator adapts seamlessly to any trading style. It offers a total of 26 long entry conditions and 26 short entry conditions, making it one of the most configurable ADX tools on TradingView. Each condition is fully adjustable, enabling the creation of statistical, quantitative, and automated strategies. You maintain full control over the signals to align perfectly with your system.
⯁ Innovative and Science-Based
This is the first public ADX indicator to apply least-squares predictive modeling to ADX dynamics. Technically, it embeds machine learning logic into a traditional trend-strength indicator. Using linear regression as a predictive engine adds powerful statistical rigor to the ADX, turning it into an intelligent, forward-looking signal generator.
⯁ Scientific Foundation: Linear Regression
Linear regression is a fundamental method in statistics and machine learning used to model the relationship between a dependent variable y and one or more independent variables x. The basic formula for simple linear regression is:
y = β₀ + β₁x + ε
Where:
y = predicted value (e.g., future ADX)
x = explanatory variable (e.g., bar index or time)
β₀ = intercept
β₁ = slope (rate of change)
ε = random error term
The goal is to estimate β₀ and β₁ by minimizing the sum of squared errors. This is achieved using the least squares method, ensuring the best linear fit to historical data. Once the coefficients are calculated, the model extends the regression line forward, generating the ADX projection based on recent trends.
⯁ Least Squares Estimation
To minimize the error, the regression coefficients are calculated as:
β₁ = Σ((xᵢ - x̄)(yᵢ - ȳ)) / Σ((xᵢ - x̄)²)
β₀ = ȳ - β₁x̄
Where:
Σ = summation
x̄ and ȳ = means of x and y
i ranges from 1 to n (number of data points)
These formulas provide the best linear unbiased estimator under Gauss-Markov conditions — assuming constant variance and linearity.
⯁ Linear Regression in Machine Learning
Linear regression is a foundational algorithm in supervised learning. Its power in producing quantitative predictions makes it essential in AI systems, predictive analytics, time-series forecasting, and automated trading. Applying it to the ADX essentially places an intelligent forecasting engine inside a classic trend tool.
⯁ Visual Interpretation
Imagine an ADX time series like this:
Time →
ADX →
The regression line smooths these values and projects them n periods forward, creating a predictive trajectory. This forecasted ADX line can intersect with the actual ADX, offering smarter buy and sell signals.
⯁ Summary of Scientific Concepts
Linear Regression: Models variable relationships with a straight line.
Least Squares: Minimizes prediction errors for best fit.
Time-Series Forecasting: Predicts future values using historical data.
Supervised Learning: Trains models to predict outcomes from inputs.
Statistical Smoothing: Reduces noise and highlights underlying trends.
⯁ Why This Indicator Is Revolutionary
Scientifically grounded: Based on rigorous statistical theory.
Unprecedented: First public ADX using least-squares forecast modeling.
Smart: Uses machine learning logic.
Forward-Looking: Generates predictive, not just reactive, signals.
Customizable: Flexible for any strategy or timeframe.
⯁ Conclusion
By merging ADX and linear regression, this indicator enables traders to predict market momentum rather than merely follow it. ADX Forecast Colorful is not just another indicator — it’s a scientific leap forward in technical analysis. With 26 fully configurable entry conditions and smart forecasting, this open-source tool is built for creating cutting-edge quantitative strategies.
⯁ Example of simple linear regression with one independent variable
This example demonstrates how a basic linear regression works when there is only one independent variable influencing the dependent variable. This type of model is used to identify a direct relationship between two variables.
⯁ In linear regression, observations (red) are considered the result of random deviations (green) from an underlying relationship (blue) between a dependent variable (y) and an independent variable (x)
This concept illustrates that sampled data points rarely align perfectly with the true trend line. Instead, each observed point represents the combination of the true underlying relationship and a random error component.
⯁ Visualizing heteroscedasticity in a scatterplot with 100 random fitted values using Matlab
Heteroscedasticity occurs when the variance of the errors is not constant across the range of fitted values. This visualization highlights how the spread of data can change unpredictably, which is an important factor in evaluating the validity of regression models.
⯁ The datasets in Anscombe’s quartet were designed to have nearly the same linear regression line (as well as nearly identical means, standard deviations, and correlations) but look very different when plotted
This classic example shows that summary statistics alone can be misleading. Even with identical numerical metrics, the datasets display completely different patterns, emphasizing the importance of visual inspection when interpreting a model.
⯁ Result of fitting a set of data points with a quadratic function
This example illustrates how a second-degree polynomial model can better fit certain datasets that do not follow a linear trend. The resulting curve reflects the true shape of the data more accurately than a straight line.
⯁ What is the ADX?
The Average Directional Index (ADX) is a technical analysis indicator developed by J. Welles Wilder. It measures the strength of a trend in a market, regardless of whether the trend is up or down.
The ADX is an integral part of the Directional Movement System, which also includes the Plus Directional Indicator (+DI) and the Minus Directional Indicator (-DI). By combining these components, the ADX provides a comprehensive view of market trend strength.
⯁ How to use the ADX?
The ADX is calculated based on the moving average of the price range expansion over a specified period (usually 14 periods). It is plotted on a scale from 0 to 100 and has three main zones:
Strong Trend: When the ADX is above 25, indicating a strong trend.
Weak Trend: When the ADX is below 20, indicating a weak or non-existent trend.
Neutral Zone: Between 20 and 25, where the trend strength is unclear.
⯁ Entry Conditions
Each condition below is fully configurable and can be combined to build precise trading logic.
📈 BUY
🅰️ Signal Validity: The signal will remain valid for X bars .
🅰️ Signal Sequence: Configurable as AND or OR .
🅰️ +DI > -DI
🅰️ +DI < -DI
🅰️ +DI > ADX
🅰️ +DI < ADX
🅰️ -DI > ADX
🅰️ -DI < ADX
🅰️ ADX > Threshold
🅰️ ADX < Threshold
🅰️ +DI > Threshold
🅰️ +DI < Threshold
🅰️ -DI > Threshold
🅰️ -DI < Threshold
🅰️ +DI (Crossover) -DI
🅰️ +DI (Crossunder) -DI
🅰️ +DI (Crossover) ADX
🅰️ +DI (Crossunder) ADX
🅰️ +DI (Crossover) Threshold
🅰️ +DI (Crossunder) Threshold
🅰️ -DI (Crossover) ADX
🅰️ -DI (Crossunder) ADX
🅰️ -DI (Crossover) Threshold
🅰️ -DI (Crossunder) Threshold
🔮 +DI (Crossover) -DI Forecast
🔮 +DI (Crossunder) -DI Forecast
🔮 ADX (Crossover) +DI Forecast
🔮 ADX (Crossunder) +DI Forecast
📉 SELL
🅰️ Signal Validity: The signal will remain valid for X bars .
🅰️ Signal Sequence: Configurable as AND or OR .
🅰️ +DI > -DI
🅰️ +DI < -DI
🅰️ +DI > ADX
🅰️ +DI < ADX
🅰️ -DI > ADX
🅰️ -DI < ADX
🅰️ ADX > Threshold
🅰️ ADX < Threshold
🅰️ +DI > Threshold
🅰️ +DI < Threshold
🅰️ -DI > Threshold
🅰️ -DI < Threshold
🅰️ +DI (Crossover) -DI
🅰️ +DI (Crossunder) -DI
🅰️ +DI (Crossover) ADX
🅰️ +DI (Crossunder) ADX
🅰️ +DI (Crossover) Threshold
🅰️ +DI (Crossunder) Threshold
🅰️ -DI (Crossover) ADX
🅰️ -DI (Crossunder) ADX
🅰️ -DI (Crossover) Threshold
🅰️ -DI (Crossunder) Threshold
🔮 +DI (Crossover) -DI Forecast
🔮 +DI (Crossunder) -DI Forecast
🔮 ADX (Crossover) +DI Forecast
🔮 ADX (Crossunder) +DI Forecast
🤖 Automation
All BUY and SELL conditions are compatible with TradingView alerts, making them ideal for fully or semi-automated systems.
⯁ Unique Features
Linear Regression: (Forecast)
Signal Validity: The signal will remain valid for X bars
Signal Sequence: Configurable as AND/OR
Condition Table: BUY/SELL
Condition Labels: BUY/SELL
Plot Labels in the Graph Above: BUY/SELL
Automate and Monitor Signals/Alerts: BUY/SELL
Background Colors: "bgcolor"
Background Colors: "fill"
Linear Regression (Forecast)
Signal Validity: The signal will remain valid for X bars
Signal Sequence: Configurable as AND/OR
Table of Conditions: BUY/SELL
Conditions Label: BUY/SELL
Plot Labels in the graph above: BUY/SELL
Automate & Monitor Signals/Alerts: BUY/SELL
Background Colors: "bgcolor"
Background Colors: "fill"
SP500 Session Gap Fade StrategySummary in one paragraph
SPX Session Gap Fade is an intraday gap fade strategy for index futures, designed around regular cash sessions on five minute charts. It helps you participate only when there is a full overnight or pre session gap and a valid intraday session window, instead of trading every open. The original part is the gap distance engine which anchors both stop and optional target to the previous session reference close at a configurable flat time, so every trade’s risk scales with the actual gap size rather than a fixed tick stop.
Scope and intent
• Markets. Primarily index futures such as ES, NQ, YM, and liquid index CFDs that exhibit overnight gaps and regular cash hours.
• Timeframes. Intraday timeframes from one minute to fifteen minutes. Default usage is five minute bars.
• Default demo used in the publication. Symbol CME:ES1! on a five minute chart.
• Purpose. Provide a simple, transparent way to trade opening gaps with a session anchored risk model and forced flat exit so you are not holding into the last part of the session.
• Limits. This is a strategy. Orders are simulated on standard candles only.
Originality and usefulness
• Unique concept or fusion. The core novelty is the combination of a strict “full gap” entry condition with a session anchored reference close and a gap distance based TP and SL engine. The stop and optional target are symmetric multiples of the actual gap distance from the previous session’s flat close, rather than fixed ticks.
• Failure mode it addresses. Fixed sized stops do not scale when gaps are unusually small or unusually large, which can either under risk or over risk the account. The session flat logic also reduces the chance of holding residual positions into late session liquidity and news.
• Testability. All key pieces are explicit in the Inputs: session window, minutes before session end, whether to use gap exits, whether TP or SL are active, and whether to allow candle based closes and forced flat. You can toggle each component and see how it changes entries and exits.
• Portable yardstick. The main unit is the absolute price gap between the entry bar open and the previous session reference close. tp_mult and sl_mult are multiples of that gap, which makes the risk model portable across contracts and volatility regimes.
Method overview in plain language
The strategy first defines a trading session using exchange time, for example 08:30 to 15:30 for ES day hours. It also defines a “flat” time a fixed number of minutes before session end. At the flat bar, any open position is closed and the bar’s close price is stored as the reference close for the next session. Inside the session, the strategy looks for a full gap bar relative to the prior bar: a gap down where today’s high is below yesterday’s low, or a gap up where today’s low is above yesterday’s high. A full gap down generates a long entry; a full gap up generates a short entry. If the gap risk engine is enabled and a valid reference close exists, the strategy measures the distance between the entry bar open and that reference close. It then sets a stop and optional target as configurable multiples of that gap distance and manages them with strategy.exit. Additional exits can be triggered by a candle color flip or by the forced flat time.
Base measures
• Range basis. The main unit is the absolute difference between the current entry bar open and the stored reference close from the previous session flat bar. That value is used as a “gap unit” and scaled by tp_mult and sl_mult to build the target and stop.
Components
• Component one: Gap Direction. Detects full gap up or full gap down by comparing the current high and low to the previous bar’s high and low. Gap down signals a long fade, gap up signals a short fade. There is no smoothing; it is a strict structural condition.
• Component two: Session Window. Only allows entries when the current time is within the configured session window. It also defines a flat time before the session end where positions are forced flat and the reference close is updated.
• Component three: Gap Distance Risk Engine. Computes the absolute distance between the entry open and the stored reference close. The stop and optional target are placed as entry ± gap_distance × multiplier so that risk scales with gap size.
• Optional component: Candle Exit. If enabled, a bullish bar closes short positions and a bearish bar closes long positions, which can shorten holding time when price reverses quickly inside the session.
• Session windows. Session logic uses the exchange time of the chart symbol. When changing symbols or venues, verify that the session time string still matches the new instrument’s cash hours.
Fusion rule
All gates are hard conditions rather than weighted scores. A trade can only open if the session window is active and the full gap condition is true. The gap distance engine only activates if a valid reference close exists and use_gap_risk is on. TP and SL are controlled by separate booleans so you can use SL only, TP only, or both. Long and short are symmetric by construction: long trades fade full gap downs, short trades fade full gap ups with mirrored TP and SL logic.
Signal rule
• Long entry. Inside the active session, when the current bar shows a full gap down relative to the previous bar (current high below prior low), the strategy opens a long position. If the gap risk engine is active, it places a gap based stop below the entry and an optional target above it.
• Short entry. Inside the active session, when the current bar shows a full gap up relative to the previous bar (current low above prior high), the strategy opens a short position. If the gap risk engine is active, it places a gap based stop above the entry and an optional target below it.
• Forced flat. At the configured flat time before session end, any open position is closed and the close price of that bar becomes the new reference close for the following session.
• Candle based exit. If enabled, a bearish bar closes longs, and a bullish bar closes shorts, regardless of where TP or SL sit, as long as a position is open.
What you will see on the chart
• Markers on entry bars. Standard strategy entry markers labeled “long” and “short” on the gap bars where trades open.
• Exit markers. Standard exit markers on bars where either the gap stop or target are hit, or where a candle exit or forced flat close occurs. Exit IDs “long_gap” and “short_gap” label gap based exits.
• Reference levels. Horizontal lines for the current long TP, long SL, short TP, and short SL while a position is open and the gap engine is enabled. They update when a new trade opens and disappear when flat.
• Session background. This version does not add background shading for the session; session logic runs internally based on time.
• No on chart table. All decisions are visible through orders and exit levels. Use the Strategy Tester for performance metrics.
Inputs with guidance
Session Settings
• Trading session (sess). Session window in exchange time. Typical value uses the regular cash session for each contract, for example “0830-1530” for ES. Adjust if your broker or symbol uses different hours.
• Minutes before session end to force exit (flat_before_min). Minutes before the session end where positions are forced flat and the reference close is stored. Typical range is 15 to 120. Raising it closes trades earlier in the day; lowering it allows trades later in the session.
Gap Risk
• Enable gap based TP/SL (use_gap_risk). Master switch for the gap distance exit engine. Turning it off keeps entries and forced flat logic but removes automatic TP and SL placement.
• Use TP limit from gap (use_gap_tp). Enables gap based profit targets. Typical values are true for structured exits or false if you want to manage exits manually and only keep a stop.
• Use SL stop from gap (use_gap_sl). Enables gap based stop losses. This should normally remain true so that each trade has a defined initial risk in ticks.
• TP multiplier of gap distance (tp_mult). Multiplier applied to the gap distance for the target. Typical range is 0.5 to 2.0. Raising it places the target further away and reduces hit frequency.
• SL multiplier of gap distance (sl_mult). Multiplier applied to the gap distance for the stop. Typical range is 0.5 to 2.0. Raising it widens the stop and increases risk per trade; lowering it tightens the stop and may increase the number of small losses.
Exit Controls
• Exit with candle logic (use_candle_exit). If true, closes shorts on bullish candles and longs on bearish candles. Useful when you want to react to intraday reversal bars even if TP or SL have not been reached.
• Force flat before session end (use_forced_flat). If true, guarantees you are flat by the configured flat time and updates the reference close. Turn this off only if you understand the impact on overnight risk.
Filters
There is no separate trend or volatility filter in this version. All trades depend on the presence of a full gap bar inside the session. If you need extra filtering such as ATR, volume, or higher timeframe bias, they should be added explicitly and documented in your own fork.
Usage recipes
Intraday conservative gap fade
• Timeframe. Five minute chart on ES regular session.
• Gap risk. use_gap_risk = true, use_gap_tp = true, use_gap_sl = true.
• Multipliers. tp_mult around 0.7 to 1.0 and sl_mult around 1.0.
• Exits. use_candle_exit = false, use_forced_flat = true. Focus on the structured TP and SL around the gap.
Intraday aggressive gap fade
• Timeframe. Five minute chart.
• Gap risk. use_gap_risk = true, use_gap_tp = false, use_gap_sl = true.
• Multipliers. sl_mult around 0.7 to 1.0.
• Exits. use_candle_exit = true, use_forced_flat = true. Entries fade full gaps, stops are tight, and candle color flips flatten trades early.
Higher timeframe gap tests
• Timeframe. Fifteen minute or sixty minute charts on instruments with regular gaps.
• Gap risk. Keep use_gap_risk = true. Consider slightly higher sl_mult if gaps are structurally wider on the higher timeframe.
• Note. Expect fewer trades and be careful with sample size; multi year data is recommended.
Properties visible in this publication
• On average our risk for each position over the last 200 trades is 0.4% with a max intraday loss of 1.5% of the total equity in this case of 100k $ with 1 contract ES. For other assets, recalculations and customizations has to be applied.
• Initial capital. 100 000.
• Base currency. USD.
• Default order size method. Fixed with size 1 contract.
• Pyramiding. 0.
• Commission. Flat 2 USD per order in the Strategy Tester Properties. (2$ buying + 2$selling)
• Slippage. One tick in the Strategy Tester Properties.
• Process orders on close. ON.
Realism and responsible publication
• No performance claims are made. Past results do not guarantee future outcomes.
• Costs use a realistic flat commission and one tick of slippage per trade for ES class futures.
• Default sizing with one contract on a 100 000 reference account targets modest per trade risk. In practice, extreme slippage or gap through events can exceed this, so treat the one and a half percent risk target as a design goal, not a guarantee.
• All orders are simulated on standard candles. Shapes can move while a bar is forming and settle on bar close.
Honest limitations and failure modes
• Economic releases, thin liquidity, and limit conditions can break the assumptions behind the simple gap model and lead to slippage or skipped fills.
• Symbols with very frequent or very large gaps may require adjusted multipliers or alternative risk handling, especially in high volatility regimes.
• Very quiet periods without clean gaps will produce few or no trades. This is expected behavior, not a bug.
• Session windows follow the exchange time of the chart. Always confirm that the configured session matches the symbol.
• When both the stop and target lie inside the same bar’s range, the TradingView engine decides which is hit first based on its internal intrabar assumptions. Without bar magnifier, tie handling is approximate.
Legal
Education and research only. This strategy is not investment advice. You remain responsible for all trading decisions. Always test on historical data and in simulation with realistic costs before considering any live use.
Market Extreme Zones IndexThe Market Extreme Zones Index is a new mean reversion (valuation) tool focused on catching long term oversold/overbought zones. Combining an enhanced RSI with a smoothed Z-score this indicator allows traders to find oppurtunities during highly oversold/overbought zones.
I will separate the explanation into the following parts:
1. How does it work?
2. Methodologies & Concepts
3. Use cases
How does it work?
The indicator attempts to catch highly unprobable events in either direction to capture reversal points over the long term. This is done by calculating the Z-Score of an enhanced RSI.
First we need to calculate the Enhanced RSI:
For this we need to calculate 2 additional lengths:
Length1 = user defined length
Length2 = Length1/2
Length3 = √Length
Now we need to calculate 3 different RSIs:
1st RSI => uses classic user defined source and classic user defined length.
2nd RSI => uses classic user defined source and Length 2.
3rd RSI => uses RSI 2 as source and Length 2
Now calculate the divergence:
RSI_base => 2nd RSI * 3 - 1st RSI - 3rd RSI
After this we need to calculate the median of the RSI_base over √Length and make a divergence of these 2:
RSI => RSI_base*2 - median
All that remains now is the Z-score calculations:
We need:
Average RSI value
Standard Deviation = a measure of how dispersed or spread out a set of data values are from their average
Z-score = (Current Value - Average Value) / Standard Deviation
After this we just smooth the Z-score with a Weighted Moving average with √Length
Methodology & Concepts
Mean Reversion Methodology:
The methodology behind mean reversion is the theory that asset prices will eventually return to their long-term average after deviating significantly, driven by the belief that extreme moves are temporary.
Z-Score Methodology:
A Z-score, or standard score, is a statistical measure that indicates how many standard deviations a data point is from the mean of a dataset. A positive z-score means the value is above the mean, a negative score means it's below, and a score of zero means the value is equal to the mean.
You might already be able to see where I am going with this:
Z-Score could be used for the extreme moves to capture reversal points.
By applying it to the RSI rather than the Price, we get a more accurate measurement that allow us to get a banger indicator.
Use Cases
Capturing reversal points
Trend Direction
- while the main use it for mean reversion, the values can indicate whether we are in an uptrend or a downtrend.
Advantages:
Visualization:
The indicator has many plots to ensure users can easily see what the indicator signals, such as highlighting extreme conditions with background colors.
Versatility:
This indicator works across multiple assets, including the S&P500 and more, so it is not only for crypto.
Final note:
No indicator alone is perfect.
Backtests are not indicative of future performance.
Hope you enjoy Gs!
Good luck!
AlgoIndexOS-ES-FuturesAlgoIndexOS — ES Futures Strategy v2.0 (5-Minute RTH)
Scope (read first)
ES on 5-minute only, RTH session. The strategy operates on U.S. Regular Trading Hours (09:30–16:00 ET) using a 5-minute ES chart. It builds an Opening Session Range (OSR) from the RTH open, then runs a breakout engine when internal quality conditions are met. Exits are target-based with an intrabar touch-to-flat safety. Positions are flattened at the RTH session end by default. Alerts can post JSON to your Webhook URL for automation.
What this is
One intraday engine with four curated presets (“Stages”) tuned for distinct segments of the NY session. Stages keep the core logic consistent while applying time-of-day context and conservative governors. Single invite-only listing; not a multi-post suite.
How it trades (high-level)
Range context: Builds and locks the OSR from the opening bell; entries only arm after the range is set.
Quality gating: Trades only when internal trend/volatility/confirmation conditions align (no parameter disclosure).
Breakout execution: Signals at bar close; bracket exits manage take-profit (limit) with an intrabar “TP-touch” safety to avoid phantom fills; optional stop-loss.
Session safety: Positions flat at RTH close by default (time exit).
(No settings or thresholds are disclosed; presets encapsulate research choices.)
Stages (session templates; one engine)
A single Stage selector chooses among four presets optimized for different parts of the RTH session (morning vs mid-day; long/short focus). Internal parameters remain fixed to preserve tested behavior.
Public inputs (kept minimal)
Stage (choose your preset)
TP / SL (points) shown for transparency; effective values are governed by the selected preset to maintain consistency with research.
Optional display overlays (status line/markers) for readability.
Alerts (how to use)
Create an alert on the strategy and choose Strategy → Order fills. Use a webhook if you want automation. The payload includes the exact chart symbol so it works on ES1! or a specific ES contract:
{
"tv_symbol": "{{ticker}}",
"tv_exchange": "{{exchange}}",
"action": "buy|sell|exit",
"price": {{close}},
"time": "{{timenow}}"
}
If your receiver needs a fixed root (e.g., “ES”), map it on your server using tv_symbol for context.
Backtest & assumptions
Backtest assumptions (initial capital, commission, slippage, margin) are user-configurable in TradingView. Results on your chart reflect your settings. This script evaluates ES fills on 5-minute RTH bars; live execution will differ.
Operating notes
Use on ES only, 5-minute timeframe, RTH session.
If you run multiple Stages, use separate charts/tabs and coordinate net exposure in your own tooling if needed.
Publish with a clean chart for clarity.
Disclosures (compliance)
No investment advice. This script is for research/education and tooling only. It does not provide investment, legal, tax, or accounting advice and does not recommend any security, instrument, or strategy. Use at your own risk.
Hypothetical performance (CFTC 4.41). Hypothetical or simulated results have many limitations, and no representation is made that any account will achieve similar outcomes. Past performance is not necessarily indicative of future results.
Futures risk. Trading futures involves substantial risk of loss and is not suitable for all investors. Leverage, gaps, slippage, and connectivity can cause losses exceeding initial investment.
Backtesting limitations. Results depend on data quality, chart resolution, session filters, and user assumptions; live execution will differ.
Intellectual property. © 2025 AlgoIndex. All Rights Reserved. Redistribution, resale, or decompilation prohibited without written consent.
BB SPY Mean Reversion Investment StrategySummary
Mean reversion first, continuation second. This strategy targets equities and ETFs on daily timeframes. It waits for price to revert from a Bollinger location with candle and EMA agreement, then manages risk with ATR based exits. Uniqueness comes from two elements working together. One, an adaptive band multiplier driven by volatility of volatility that expands or contracts the envelope as conditions change. Two, a bias memory that re arms the same direction after any stop, target, or time exit until a true opposite signal appears. Add it to a clean chart, use the markers and levels, and select on bar close for conservative alerts. Shapes can move while the bar is open and settle on close.
Scope and intent
• Markets. Currently adapted for SPY, needs to be optimized for other assets
• Timeframes. Daily primary. Other frames are possible but not the default
• Default demo. SPY on daily
• Purpose. Trade mean reversion entries that can chain into a longer swing by splitting holds into ATR or time segments
Originality and usefulness
• Novelty. Adaptive band width from volatility of volatility plus a persistent bias array that keeps the original direction alive across sequential entries until an opposite setup is confirmed
• Failure modes mitigated. False starts in chop are reduced by candle color and EMA location. Missed continuation after a take profit or stop is addressed by the re arm engine. Oversized envelopes during quiet regimes are avoided by the adaptive multiplier
• Testability. Every module has Inputs and visible levels so users can see why a suggestion appears
• Portable yardstick. All risk and targets are expressed in ATR units
Method overview in plain language
The engine measures where price sits relative to Bollinger bands, confirms with candle color and EMA location, requires ADX for shorts(in our case long close since we use it currently as long only), and optionally requires a trend or mean reversion regime using band width percent rank and basis slope. Risk uses ATR for stop, target, and optional breakeven. A small array stores the last confirmed direction. While flat, the engine keeps a pending order in that direction. The array flips only when a true opposite setup appears.
Base measures
• Range basis. True Range smoothed over a user defined ATR Length
• Return basis. Not required
Components
• Bollinger envelope. SMA length and standard deviation multiplier. Entry is based on cross of close through the band with location bias
• Candle and EMA filter. Close relative to open and close relative to EMA align direction
• ADX gate for shorts. Requires minimum trend strength for short trades
• Adaptive multiplier. Band width scales using volatility of volatility so envelopes breathe with conditions
• Regime gate optional. Band width percent rank and basis slope identify trend or mean reversion regimes
• Risk manager. ATR stop, ATR target, optional breakeven, optional time exit
• Bias memory. Array stores last confirmed direction and re arms entries while flat
Fusion rule
Minimum satisfied gates count style. All required gates must be true. Optional gates are controlled in Inputs. Bias memory never overrides an opposite confirmed setup.
Signal rule
• Long setup when close crosses up through the lower band, the bar closes green, and close is above the long EMA
• Short setup when close crosses down through the upper band, the bar closes red, close is below the short EMA, and ADX is above the minimum
• While flat the model keeps a pending order in the stored direction until a true opposite setup appears
• IN LONG or IN SHORT describes states between entry and exit
What you will see on the chart
• Markers for Long and Short setups
• Exit markers from ATR or time rules
• Reference levels for entry, stop, and target
• Bollinger bands and optional adaptive bands
Inputs with guidance
Setup
• Signal timeframe. Uses the chart timeframe
• Invert direction optional. Flips long and short
Logic
• BB Length. Typical 10 to 50. Higher smooths more
• BB Mult. Typical 1.0 to 2.5. Higher widens entries
• EMA Length long. Typical 10 to 50
• EMA Length short. Typical 5 to 30
• ADX Minimum for short. Typical 15 to 35
Filters
• Regime Type. none or trend or mean reversion
• Rank Lookback. Typical 100 to 300
• Basis Slope Length and Threshold. Larger values reduce false trends
Risk
• ATR Length. Typical 10 to 21
• ATR Stop Mult. Typical 1.0 to 3.0
• ATR Take Profit Mult. Typical 2.0 to 5.0
• Breakeven Trigger R. Move stop to entry after the chosen multiple
• Time Exit. Minimum bars and extension when profit exceeds a fraction of ATR
Bias and rearm
• Bias flips kept. Array depth
• Keep rearm when flat. Maintain a pending order while flat
UI
• Show markers and levels. Clean defaults
Usage recipes
Alerts update in real time and can change while the bar forms. Select on bar close for conservative workflows.
Properties visible in this publication
• Initial capital 25000
• Base currency USD
• If any higher timeframe calls are enabled, request.security uses lookahead off
• Commission 0.03 percent
• Slippage 3 ticks
• Default order size method Percent of equity with value 5
• Pyramiding 0
• Process orders on close On
• Bar magnifier Off
• Recalculate after order is filled Off
• Calc on every tick Off
Realism and responsible publication
No performance claims. Costs and fills vary by venue. Shapes can move intrabar and settle on close. Strategies use standard candles only.
Honest limitations and failure modes
High impact releases and thin liquidity can break assumptions. Gap heavy symbols may require larger ATR. Very quiet regimes can reduce contrast in the mean reversion signal. If stop and target can both be touched inside one bar, outcome follows the TradingView order model for that bar path.
Regimes with extreme one sided trend and very low volatility can reduce mean reversion edges. Results vary by symbol and venue. Past results never guarantee future outcomes.
Open source reuse and credits
None.
Backtest realism
Costs are realistic for liquid equities. Sizing does not exceed five percent per trade by default. Any departure should be justified by the user.
If you got any questions please le me know
Grizzly Brahman · PRO SCALPERGrizzly Brahman TMAX 4 is a fourth-generation Trend-Momentum-Adaptive Crossover system built to identify true intraday direction and volatility alignment before price acceleration begins.
It combines adaptive moving-average bands, momentum filtration, and trend-fill logic to produce crystal-clear long/short zones directly on the chart.
Preset Modes
“Aggressive / Balanced / Disciplined” presets optimize responsiveness for scalping, intra-day, or swing conditions.
Session Shading & ORB Levels
Optional overlays for Opening Range Breakout, Pre-Market High/Low, and Previous Day High/Low to frame liquidity targets.
Heikin Ashi Compatibility
Optimized to read momentum flow cleanly on Heikin Ashi charts for false-breakout filtering.
Momentum Bands
Adaptive outer bands act as over-extension or “take-profit” zones — similar to ATR channels but smoothed for consistency.
How to Use
Identify Trend Zone — watch for color fill change and TMA alignment.
Enter on Marker Confirmation — green triangle = long momentum confirm, red triangle = short.
Manage Risk around outer TMA/ATR band touches or when color intensity fades.
Combine with GB Set-Up & Confirmation (lower pane) for dual-signal entry validation.
Lump Sum Favorability (SPX & NDX)This indicator provides a visual dashboard to gauge the statistical favorability of deploying a "Lump Sum" investment into the SPX (S&P 500) or NDX (Nasdaq 100).
The primary goal is not to time the exact market bottom, but to identify zones of significant pessimism or euphoria. Historically, periods of indiscriminate selling have represented high-probability entry points for long-term investors.
The dashboard consists of two parts:
1. The Favorability Gauge: A 12-segment gauge that moves from Red (Unfavorable) to Teal (Favorable).
2. The Summary Text: An optional text box (enabled in settings) that provides a plain-English summary of the current market breadth.
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The Method: Market Breadth
This indicator is not based on the price of the index itself. Price-based indicators (like an RSI on the SPX) can be misleading. In a market-cap-weighted index, a few mega-cap stocks can hold the index price up while the vast majority of "average" stocks are already in a deep bear market.
This tool uses Market Breadth to measure the true, underlying health and participation of the entire market.
How It Works
1. Data Source: The indicator pulls the daily percentage of companies within the selected index (SPX or NDX) that are trading above their 200-day moving average. (Data tickers: S5TH for SPX, NDTH for NDX).
2. Smoothing: This raw data is volatile. To filter out daily noise and confirm a persistent trend, the indicator calculates a 5-day Simple Moving Average (SMA) of this percentage. This is the value used by the indicator.
3. Interpretation:
High Value (>= 50%): More than half of the stocks are above their long-term average. This signifies the market is "Overheated" or in a risk-on phase. The favorability for a new lump sum investment is considered Low.
Low Value (< 50%): Less than half of the stocks are above their long-term average. This signifies "Oversold" conditions or capitulation. These moments historically offer the best favorability for starting a new long-term investment.
---
How to Use the Indicator
1. The Favorability Gauge
The gauge is designed to be intuitive: Red means "Stop/Caution," and Teal means "Go/Opportunity."
Note: The gauge's logic is inverted from the data value to achieve this simplicity.
Red Zone (Left): UNFAVORABLE
This corresponds to a high percentage of stocks being above their 200d MA (>= 50%). The market is considered Overheated, and the favorability for a new lump sum investment is low.
Teal Zone (Right): FAVORABLE
This corresponds to a low percentage of stocks being above their 200d MA (< 50%). The market is considered Oversold, and the favorability for a new lump sum investment is high.
2. The Summary Text
When "Show Summary Text" is enabled in the settings, a box will appear at the top-center of your chart. This box provides a clear, data-driven summary, such as:
"Currently, only 22% of S&P 500 companies are above their 200-day MA. Market is Oversold."
The color of this text will automatically change to match the market state (Red for Overheated, Teal for Oversold), providing instant confirmation of the gauge's reading.
---
Settings
Market: Choose the index to analyze: SPX (S&P 500) or NDX (Nasdaq 100).
Gauge Position: Select where the gauge dashboard should appear on your chart (default is Bottom Right).
Show Summary Text: Toggle the descriptive text box on or off (default is On).
---
This indicator is a statistical and historical guide, not a financial advice or timing signal. It is designed to measure favorability based on past market behavior, not to provide certainty.
Extreme oversold conditions can persist, and markets can always go lower. This tool should be used as one component of a broader investment and risk-management framework. Past performance is not a guarantee of future results.
TriAnchor Elastic Reversion US Market SPY and QQQ adaptedSummary in one paragraph
Mean-reversion strategy for liquid ETFs, index futures, large-cap equities, and major crypto on intraday to daily timeframes. It waits for three anchored VWAP stretches to become statistically extreme, aligns with bar-shape and breadth, and fades the move. Originality comes from fusing daily, weekly, and monthly AVWAP distances into a single ATR-normalized energy percentile, then gating with a robust Z-score and a session-safe gap filter.
Scope and intent
• Markets: SPY QQQ IWM NDX large caps liquid futures liquid crypto
• Timeframes: 5 min to 1 day
• Default demo: SPY on 60 min
• Purpose: fade stretched moves only when multi-anchor context and breadth agree
• Limits: strategy uses standard candles for signals and orders only
Originality and usefulness
• Unique fusion: tri-anchor AVWAP energy percentile plus robust Z of close plus shape-in-range gate plus breadth Z of SPY QQQ IWM
• Failure mode addressed: chasing extended moves and fading during index-wide thrusts
• Testability: each component is an input and visible in orders list via L and S tags
• Portable yardstick: distances are ATR-normalized so thresholds transfer across symbols
• Open source: method and implementation are disclosed for community review
Method overview in plain language
Base measures
• Range basis: ATR(length = atr_len) as the normalization unit
• Return basis: not used directly; we use rank statistics for stability
Components
• Tri-Anchor Energy: squared distances of price from daily, weekly, monthly AVWAPs, each divided by ATR, then summed and ranked to a percentile over base_len
• Robust Z of Close: median and MAD based Z to avoid outliers
• Shape Gate: position of close inside bar range to require capitulation for longs and exhaustion for shorts
• Breadth Gate: average robust Z of SPY QQQ IWM to avoid fading when the tape is one-sided
• Gap Shock: skip signals after large session gaps
Fusion rule
• All required gates must be true: Energy ≥ energy_trig_prc, |Robust Z| ≥ z_trig, Shape satisfied, Breadth confirmed, Gap filter clear
Signal rule
• Long: energy extreme, Z negative beyond threshold, close near bar low, breadth Z ≤ −breadth_z_ok
• Short: energy extreme, Z positive beyond threshold, close near bar high, breadth Z ≥ +breadth_z_ok
What you will see on the chart
• Standard strategy arrows for entries and exits
• Optional short-side brackets: ATR stop and ATR take profit if enabled
Inputs with guidance
Setup
• Base length: window for percentile ranks and medians. Typical 40 to 80. Longer smooths, shorter reacts.
• ATR length: normalization unit. Typical 10 to 20. Higher reduces noise.
• VWAP band stdev: volatility bands for anchors. Typical 2.0 to 4.0.
• Robust Z window: 40 to 100. Larger for stability.
• Robust Z entry magnitude: 1.2 to 2.2. Higher means stronger extremes only.
• Energy percentile trigger: 90 to 99.5. Higher limits signals to rare stretches.
• Bar close in range gate long: 0.05 to 0.25. Larger requires deeper capitulation for longs.
Regime and Breadth
• Use breadth gate: on when trading indices or broad ETFs.
• Breadth Z confirm magnitude: 0.8 to 1.8. Higher avoids fighting thrusts.
• Gap shock percent: 1.0 to 5.0. Larger allows more gaps to trade.
Risk — Short only
• Enable short SL TP: on to bracket shorts.
• Short ATR stop mult: 1.0 to 3.0.
• Short ATR take profit mult: 1.0 to 6.0.
Properties visible in this publication
• Initial capital: 25000USD
• Default order size: Percent of total equity 3%
• Pyramiding: 0
• Commission: 0.03 percent
• Slippage: 5 ticks
• Process orders on close: OFF
• Bar magnifier: OFF
• Recalculate after order is filled: OFF
• Calc on every tick: OFF
• request.security lookahead off where used
Realism and responsible publication
• No performance claims. Past results never guarantee future outcomes
• Fills and slippage vary by venue
• Shapes can move during bar formation and settle on close
• Standard candles only for strategies
Honest limitations and failure modes
• Economic releases or very thin liquidity can overwhelm mean-reversion logic
• Heavy gap regimes may require larger gap filter or TR-based tuning
• Very quiet regimes reduce signal contrast; extend windows or raise thresholds
Open source reuse and credits
• None
Strategy notice
Orders are simulated by TradingView on standard candles. request.security uses lookahead off where applicable. Non-standard charts are not supported for execution.
Entries and exits
• Entry logic: as in Signal rule above
• Exit logic: short side optional ATR stop and ATR take profit via brackets; long side closes on opposite setup
• Risk model: ATR-based brackets on shorts when enabled
• Tie handling: stop first when both could be touched inside one bar
Dataset and sample size
• Test across your visible history. For robust inference prefer 100 plus trades.
FluxGate Daily Swing StrategySummary in one paragraph
FluxGate treats long and short as different ecosystems. It runs two independent engines so the long side can be bold when the tape rewards upside persistence while the short side can stay selective when downside is messy. The core reads three directional drivers from price geometry then removes overlap before gating with clean path checks. The complementary risk module anchors stop distance to a higher timeframe ATR so a unit means the same thing on SPY and BTC. It can add take profit breakeven and an ATR trail that only activates after the trade earns it. If a stop is hit the strategy can re enter in the same direction on the next bar with a daily retry cap that you control. Add it to a clean chart. Use defaults to see the intended behavior. For conservative workflows evaluate on bar close.
Scope and intent
• Markets. Large cap equities and liquid ETFs major FX pairs US index futures and liquid crypto pairs
• Timeframes. From one minute to daily
• Default demo in this publication. SPY on one day timeframe
• Purpose. Reduce false starts without missing sustained trends by fusing independent drivers and suppressing activity when the path is noisy
• Limits. This is a strategy. Orders are simulated on standard candles. Non standard chart types are not supported for execution
Originality and usefulness
• Unique fusion. FluxGate extracts three drivers that look at price from different angles. Direction measures slope of a smoothed guide and scales by realized volatility so a point of slope does not mean a different thing on different symbols. Persistence looks at short sign agreement to reward series of closes that keep direction. Curvature measures the second difference of a local fit to wake up during convex pushes. These three are then orthonormalized so a strong reading in one does not double count through another.
• Gates that matter. Efficiency ratio prefers direct paths over treadmills. Entropy turns up versus down frequency into an information read. Light fractal cohesion punishes wrinkly paths. Together they slow the system in chop and allow it to open up when the path is clean.
• Separate long and short engines. Threshold tilts adapt to the skew of score excursions. That lets long engage earlier when upside distribution supports it and keeps short cautious where downside surprise and venue frictions are common.
• Practical risk behavior. Stops are ATR anchored on a higher timeframe so the unit is portable. Take profit is expressed in R so two R means the same concept across symbols. Breakeven and trailing only activate after a chosen R so early noise does not squeeze a good entry. Re entry after stop lets the system try again without you babysitting the chart.
• Testability. Every major window and the aggression controls live in Inputs. There is no hidden magic number.
Method overview in plain language
Base measures
• Return basis. Natural log of close over prior close for stability and easy aggregation through time. Realized volatility is the standard deviation of returns over a moving window.
• Range basis for risk. ATR computed on a higher timeframe anchor such as day week or month. That anchor is steady across venues and avoids chasing chart specific quirks.
Components
• Directional intensity. Use an EMA of typical price as a guide. Take the day to day slope as raw direction. Divide by realized volatility to get a unit free measure. Soft clip to keep outliers from dominating.
• Persistence. Encode whether each bar closed up or down. Measure short sign agreement so a string of higher closes scores better than a jittery sequence. This favors push continuity without guessing tops or bottoms.
• Curvature. Fit a short linear regression and compute the second difference of the fitted series. Strong curvature flags acceleration that slope alone may miss.
• Efficiency gate. Compare net move to path length over a gate window. Values near one indicate direct paths. Values near zero indicate treadmill behavior.
• Entropy gate. Convert up versus down frequency into a probability of direction. High entropy means coin toss. The gate narrows there.
• Fractal cohesion. A light read of path wrinkliness relative to span. Lower cohesion reduces the urge to act.
• Phase assist. Map price inside a recent channel to a small signed bias that grows with confidence. This helps entries lean toward the right half of the channel without becoming a breakout rule.
• Shock control. Compare short volatility to long volatility. When short term volatility spikes the shock gate temporarily damps activity so the system waits for pressure to normalize.
Fusion rule
• Normalize the three drivers after removing overlap
• Blend with weights that adapt to your aggression input
• Multiply by the gates to respect path quality
• Smooth just enough to avoid jitter while keeping timing responsive
• Compute an adaptive mean and deviation of the score and set separate long and short thresholds with a small tilt informed by skew sign
• The result is one long score and one short score that can cross their thresholds at different times for the same tape which is a feature not a bug
Signal rule
• A long suggestion appears when the long score crosses above its long threshold while all gates are active
• A short suggestion appears when the short score crosses below its short threshold while all gates are active
• If any required gate is missing the state is wait
• When a position is open the status is in long or in short until the complementary risk engine exits or your entry mode closes and flips
Inputs with guidance
Setup Long
• Base length Long. Master window for the long engine. Typical range twenty four to eighty. Raising it improves selectivity and reduces trade count. Lowering it reacts faster but can increase noise
• Aggression Long. Zero to one. Higher values make thresholds more permissive and shorten smoothing
Setup Short
• Base length Short. Master window for the short engine. Typical range twenty eight to ninety six
• Aggression Short. Zero to one. Lower values keep shorts conservative which is often useful on upward drifting symbols
Entries and UI
• Entry mode. Both or Long only or Short only
Complementary risk engine
• Enable risk engine. Turns on bracket exits while keeping your signal logic untouched
• ATR anchor timeframe. Day Week or Month. This sets the structural unit of stop distance
• ATR length. Default fourteen
• Stop multiple. Default one point five times the anchor ATR
• Use take profit. On by default
• Take profit in R. Default two R
• Breakeven trigger in R. Default one R
Usage recipes
Intraday trend focus
• Entry mode Both
• ATR anchor Week
• Aggression Long zero point five Aggression Short zero point three
• Stop multiple one point five Take profit two R
• Expect fewer trades that stick to directional pushes and skip treadmill noise
Intraday mean reversion focus
• Session windows optional if you add them in your copy
• ATR anchor Day
• Lower aggression both sides
• Breakeven later and trailing later so the first bounce has room
• This favors fade entries that still convert into trends when the path stays clean
Swing continuation
• Signal timeframe four hours or one day
• Confirm timeframe one day if you choose to include bias
• ATR anchor Week or Month
• Larger base windows and a steady two R target
• This accepts fewer entries and aims for larger holds
Properties visible in this publication
• Initial capital 25.000
• Base currency USD
• Default order size percent of equity value three - 3% of the total capital
• Pyramiding zero
• Commission zero point zero three percent - 0.03% of total capital
• Slippage five ticks
• Process orders on close off
• Recalculate after order is filled off
• Calc on every tick off
• Bar magnifier off
• Any request security calls use lookahead off everywhere
Realism and responsible publication
• No performance promises. Past results never guarantee future outcomes
• Fills and slippage vary by venue and feed
• Strategies run on standard candles only
• Shapes can update while a bar is forming and settle on close
• Keep risk per trade sensible. Around one percent is typical for study. Above five to ten percent is rarely sustainable
Honest limitations and failure modes
• Sudden news and thin liquidity can break assumptions behind entropy and cohesion reads
• Gap heavy symbols often behave better with a True Range basis for risk than a simple range
• Very quiet regimes can reduce score contrast. Consider longer windows or higher thresholds when markets sleep
• Session windows follow the exchange time of the chart if you add them
• If stop and target can both be inside a single bar this strategy prefers stop first to keep accounting conservative
Open source reuse and credits
• No reused open source beyond public domain building blocks such as ATR EMA and linear regression concepts
Legal
Education and research only. Not investment advice. You are responsible for your decisions. Test on history and in simulation with realistic costs
ProbRSI Adaptive SPY and QQQ Swing One Hour Strategy Summary in one paragraph
A probabilistic RSI engine for large cap ETFs and index names on intraday and swing timeframes. It converts ATR scaled returns into a 0 to 100 probability line, adapts its smoothing from path efficiency, and gates flips with simple percent levels. It is original because it fuses three pieces that traders rarely combine in one signal line: ATR normalized return probability, curvature compression, and per bar adaptive EMA. Add it to a clean chart, keep the default one hour signal on QQQ, and read the entry and exit markers generated by the strategy. For conservative alerts select on bar close.
Scope and intent
• Markets. Major ETFs and large cap equities. Index futures. Liquid crypto. Major FX pairs
• Timeframes. One minute to daily. Defaults to one hour for swing pace
• Default demo used in this publication. SPY/QQQ on one hour
• Purpose. Reduce false flips by adapting to path efficiency and by gating long and short separately
• Limits. This is a strategy. Orders are simulated on standard candles only
Originality and usefulness
• Unique fusion. Logistic probability of ATR scaled returns with arcsine pre transform, optional curvature compression, and per bar adaptive EMA steered by an efficiency ratio
• Failure mode addressed. Fast whips in congestion and late entries after spikes
• Testability. Each component has a named input and can be tuned directly. Entry names Long and Short are visible in the list of trades
• Portable yardstick. ATR scaled return is a common unit across symbols and venues
• Protected rationale. The code stays protected to preserve implementation details of the adaptive engine and curvature assist while the method and usage are fully explained here for community review
Method overview in plain language
You convert raw returns into a probability scale, adapt the smoothing to the straightness of the path, and only allow flips when a simple gate is satisfied. The probability line crosses its own EMA to generate signals. When the cross happens below a short gate or above a long gate, the flip is allowed. Otherwise it is ignored.
Base measures
• Return basis. Close minus prior close normalized by ATR, then arcsine to damp large steps. ATR window is set by ATR length. Sensitivity is adjusted by an ATR scale input
• Probability map. A logistic function maps the normalized return to 0 to 1 which becomes 0 to 100 after scaling
Components
• Probability core. Logistic probability of ATR scaled returns. Higher values imply upside pressure. Smoothed by an adaptive EMA
• Curvature assist optional. A curvature proxy compresses extreme spikes toward neutral. Useful after news bars. Weight controls strength
• Efficiency ratio. A path efficiency score from 0 to 1 extends the smoothing length during noisy paths and shortens it during directional paths
• Signal line. An EMA of the probability line creates the reference for cross up and cross down
• Gates. Two simple percent levels define when long and short flips are allowed
Fusion rule
• The adaptive EMA length is computed as a linear map between a minimum and a maximum bound based on one minus efficiency
• If curvature assist is enabled the probability is adjusted by a small counter spike term
• Final probability is compared to its EMA
Signal rule
• Long. A long entry is suggested when probability crosses above the signal line and the current probability is above the Long gate level
• Short. A short entry is suggested when probability crosses below the signal line and the current probability is below the Short gate level
• Exit and flip. When an opposite entry condition appears the current position is closed and a new position opens in the opposite direction
What you will see on the chart
• Strategy markers on suggestion bars. Orders named Long and Short
• Exit marker when the opposite signal closes the open side
• No table by design. All tuning lives in Inputs for a clean chart
Inputs with guidance
Market TF
• Symbol. Series used for oscillator computation. Use the instrument you trade or a close proxy
• Signal timeframe. Timeframe where the oscillator is evaluated. Leave blank to follow the chart
Core
• Price source. Series used for returns. Typical choice close
• Base length. Fallback EMA length used when adaptation is off. Typical range 20 to 200. Larger smooths more
• ATR length. Window for ATR that scales returns. Typical range 10 to 30. Larger normalizes more and lowers sensitivity
• Logit sharpness. Steepness of the logistic link. Typical range 1 to 8. Raising it reacts more to the same input
• ATR scale. Extra divisor on ATR. Typical range 0.5 to 2. Smaller is more sensitive
• Signal length. EMA of the probability line. Typical range 5 to 20. Larger gives fewer flips
• Long gate. Allow long flips only above this level. Typical range 20 to 40
• Short gate. Allow short flips only below this level. Typical range 20 to 40
Adaptive
• Adaptive smoothing. If on, the efficiency ratio controls the per bar EMA length
• Min effective length. Lower bound of adaptive EMA. Typical range 5 to 50
• Max effective length. Upper bound of adaptive EMA. Typical range 50 to 300
• Efficiency window. Window for efficiency ratio. Typical range 30 to 100
Shape Assist
• Curvature influence. If on, extreme spikes are nudged toward neutral
• Curvature weight. Strength of compression. Typical range 0.1 to 0.3
Properties visible in this publication
• Initial capital. 25000
• Base currency. USD
• request.security lookahead off everywhere
• Commission. 0.03 percent
• Slippage. 5 ticks
• Default order size method percent of equity with value 3 for realistic testing
• Pyramiding 0
• Process orders on close ON
• Bar magnifier OFF
• Recalculate after order is filled OFF
• Calc on every tick OFF
Realism and responsible publication
• No performance claims. Past results never guarantee future outcomes
• Shapes can move while a bar forms and settle on close
• Strategies use standard candles for signals and orders only
Honest limitations and failure modes
• Economic releases and thin liquidity can break assumptions behind the curvature assist
• Gap heavy symbols may prefer a longer ATR window
• Very quiet regimes can reduce signal contrast. Consider higher gates or longer signal length
• Session time follows the exchange of the chart and can change symbol to symbol
• Symbol sensitivity is expected. Use the gates and length inputs to find stable settings
• Past results never guarantee future outcomes
Open source reuse and credits
• None
Mode
Public protected. Source is hidden while access is free. Implementation detail remains private. Method and use are fully disclosed here
Legal
Education and research only. Not investment advice. You are responsible for your decisions. Test on historical data and in simulation before any live use. Use realistic costs.
TwinPulse Q Lead SPY x QQQ Intermarket Pulse 1HTwinPulse Q Lead is a concise one hour indicator for SPY and QQQ that converts three sources of market information into a single pulse line, a mode readout with BUY SELL WAIT, and compact alerts. It blends intermarket leadership between QQQ and SPY, intraday flow from the slope of session VWAP, and where the current price sits inside the regular trading hours range. The three components are normalized, fused, compressed to a stable range, and smoothed for clear thresholds. The aim is a readable intraday regime signal that helps you decide when to participate and when to stand aside.
The script is built with Pine v6, uses request security with lookahead off, and does not repaint. It is an indicator, not a strategy. It does not contain any solicitation, links, or outside references. The description is self contained and explains both logic and use so that any trader can understand the design without reading code.
What makes this original and useful
Intermarket leadership is measured directly from QQQ and SPY on your working timeframe using a Z score of the return spread. When growth is leading value heavy large caps, leadership turns positive. When it lags, leadership turns negative. This gives a real time read of the Nasdaq versus S and P tug of war that most day traders watch informally.
Intraday flow is taken from the slope of the session VWAP. A linear regression of VWAP over a short window captures whether value is rising or falling inside the day. Dividing by ATR normalizes slope by typical movement so that the signal is comparable across weeks.
Session position places price inside the current regular hours high to low. It answers whether the day is trading in the top half, the bottom half, or the middle. This is a simple but powerful context filter for breakouts and fades.
The three components are fused into one pulse, compressed with either hyperbolic tangent or softsign to keep values bounded, and then smoothed by a short EMA. This yields a stable range with a zero line so the eye can read shifts quickly.
The panel shows a human readable mode with reasons and a strength score. Traders who do not want to read lines can rely on a simple state and a compact justification that explains why the state is set.
This is not a mashup that simply overlays unrelated indicators. Each component was chosen to answer a distinct question that is common to SPY and QQQ intraday decision making. Leadership answers who is in charge, flow answers whether value inside the session is building or leaking, and position answers if price is pressing the extremes or circling the middle. The pulse ties the three together and prevents any single component from dominating.
How the calculations work
Leadership. Compute a short rate of change for SPY and QQQ. Subtract SPY from QQQ to get spread returns, then compute a rolling Z score over a longer window. Positive values mean QQQ is leading. Negative values mean SPY is leading.
Flow. Compute session VWAP on the active symbol. Regress VWAP over a short window to obtain a slope estimate. Divide by ATR to scale slope by current volatility so that a small rise on a quiet day is not treated the same as a small rise on a wild day.
Position. Track the highest high and lowest low since the start of regular hours. Place the current close inside that range on a zero to one scale, then recenter to a minus one to plus one scale. Positive means the top half of the day, negative means the bottom half.
Fusion. Multiply each component by a weight so users can emphasize or de emphasize leadership, flow, or position. Sum to a raw pulse.
Compression. Pass the raw pulse through a bounded function. Hyperbolic tangent is smooth and has natural saturation near the extremes. Softsign is faster and behaves like a smoother version of sign near zero. Compression avoids unbounded excursions and makes thresholds meaningful across days.
Smoothing. Apply a short EMA to the compressed pulse to reduce noise. This creates the main line called TwinPulse in the plot.
Thresholds. You can use static symmetric levels or adaptive levels. The adaptive option computes a mean and a standard deviation of the smoothed pulse over a user window, then sets upper and lower thresholds as mean plus or minus sigma times standard deviation. This allows thresholds to adjust across regimes. Static levels are still available for traders who want repeatable levels.
Events and mode. A long event fires when the smoothed pulse crosses the upper threshold with positive flow and any optional filters agree. A short event fires on the symmetric condition. The mode reads the current state rather than fire and forget. It returns BUY when the smoothed pulse is above the upper threshold with positive flow, SELL when the smoothed pulse is below the lower threshold with negative flow, otherwise WAIT. A cooldown controls how often events can fire so alerts do not spam during choppy periods.
Inputs and default values
The script ships with defaults chosen for SPY and QQQ on one hour charts.
Symbols. SPY and QQQ by default. You can switch to any pair. Many users may test IWM versus SPY for small cap reads.
Regular hours selector. On by default. This restricts the position factor to New York regular hours. Turn it off if you prefer full session behavior.
ROC length is three bars. Z score length is fifty bars. VWAP slope window is ten bars. ATR length is fourteen bars. Pulse smoothing length is three bars.
Compression mode. Choose hyperbolic tangent or softsign. Hyperbolic tangent is default.
Weights. Leadership and flow are one by default. Position is set to zero point seven to give a modest influence to where price sits inside the day.
Thresholds. Adaptive thresholds are on by default with a lookback of one hundred bars and a sigma width of zero point eight. Static levels at plus or minus zero point six are ready if you disable adaptive mode.
Filters. ADX filter is off by default. If you enable it, the script requires ADX above a user minimum before it will signal. Higher time frame confirmation is off by default. When enabled it compares the smoothed pulse on the confirm timeframe to zero and requires alignment for longs or shorts.
Cooldown. Three bars by default so that alerts do not trigger too frequently.
UI. Bar coloring is on by default. The panel is on by default and sits at the top right.
All request security calls use lookahead off and will not request future data. All persistent state variables are assigned in a way that prevents repainting. The indicator does not use non standard chart types in its logic.
How to use the indicator
Load a one hour chart of SPY or QQQ. Keep a clean chart so that the script output is easy to read.
Turn on regular hours if you want the session position to reflect the cash session. This is recommended for SPY and QQQ.
Watch the panel. Mode reads BUY or SELL or WAIT. The strength value is a simple vote based score that ranges from zero to one hundred. It counts leadership, flow, ADX if enabled, and higher time frame confirmation if enabled. You can use strength to filter weak states.
Consider action only when mode is BUY or SELL and the signal has not just fired on the last bar. The triangles mark where an event fired. Alerts use the same logic as the events. WAIT means stand aside.
To slow the system, enable ADX and set a higher minimum or enable higher time frame confirmation. To speed it up, disable the filters, disable adaptive thresholds, or tighten the sigma width.
When publishing, use a clean chart with only this indicator. Show the symbol and timeframe clearly and make sure the plot legend is visible. If you add drawings on the chart, only include ones that help readers understand the output.
Publication notes and compliance
This description is written in English. The title uses ASCII and only uses capital letters for common abbreviations. The script is original and explains how and why the components work together. There are no links or promotional material. The script does not claim performance. It does not use lookahead. The panel and alerts exist to help a human read and act with discipline. The indicator can be published as open source or as protected. If you choose protected, the description still allows readers to understand how the logic works without access to the code.
If you later convert the logic into a strategy for publication, use realistic commission and slippage, risk no more than a small share of equity per trade, and choose a dataset that yields a large enough sample. Explain any deviations from these default recommendations in your strategy description. Do not publish results from non standard chart types since they can mislead readers on signal timing.
Limitations and risks
Intermarket leadership is a relative measure. There are hours when both SPY and QQQ fall while leadership remains positive. Treat leadership as a context, not a stand alone trigger.
VWAP slope is a path measure inside the session. It can flip several times on a choppy day. That is why the script uses a short smoothing and an optional cooldown. Use ADX or higher time frame confirmation to avoid the worst chop.
Session position assumes a meaningful regular hours range. On half days or around openings with gaps the position factor can be less informative. If this bothers you, reduce the weight of position or turn it off.
Compression and smoothing introduce lag by design. The goal is stability and clarity. If you want earlier but noisier signals, reduce smoothing and weights, and use static thresholds.
No indicator guarantees future results. TwinPulse Q Lead is a decision aid. It should be combined with your risk rules, position size policy, and a clear exit plan. Past behavior is not a promise for the future.
Frequently asked questions
What symbols are supported. Any symbol can be used as the chart symbol. Leadership uses the two user symbols which default to SPY and QQQ. Many traders may try IWM versus SPY or DIA versus SPY.
Can I change the timeframe. Yes, but the design target is one hour. On very short timeframes the VWAP slope becomes very sensitive and you should consider stronger filters.
Does the script repaint. No. It uses request security with lookahead off and the panel updates on the last bar only. Events are based on bar close conditions unless you attach alerts on any alert function call which will still respect the logic without looking into the future.
How are the strength numbers built. The strength score is the share of aligned votes across leadership, flow, ADX if enabled, and higher time frame confirmation if enabled. A value near one hundred means many filters agree. A value near fifty means partial alignment. It is not a probability or an accuracy number.
Can I use non standard chart types. You can view the indicator on them but do not publish signals from non standard chart types because that can mislead readers about timing. Use classic candles or bars when you publish and when you test.
Why do I sometimes see BUY but the price is not moving. A BUY mode requires pulse above the upper threshold and positive flow. It does not require higher highs immediately. Treat BUY as a permission to look for entries using your own execution rules.
MACD Forecast [Titans_Invest]MACD Forecast — The Future of MACD in Trading
The MACD has always been one of the most powerful tools in technical analysis.
But what if you could see where it’s going, instead of just reacting to what has already happened?
Introducing MACD Forecast — the natural evolution of the MACD Full , now taken to the next level. It’s the world’s first MACD designed not only to analyze the present but also to predict the future behavior of momentum.
By combining the classic MACD structure with projections powered by Linear Regression, this indicator gives traders an anticipatory, predictive view, redefining what’s possible in technical analysis.
Forget lagging indicators.
This is the smartest, most advanced, and most accurate MACD ever created.
🍟 WHY MACD FORECAST IS REVOLUTIONARY
Unlike the traditional MACD, which only reflects current and past price dynamics, the MACD Forecast uses regression-based projection models to anticipate where the MACD line, signal line, and histogram are heading.
This means traders can:
• See MACD crossovers before they happen.
• Spot trend reversals earlier than most.
• Gain an unprecedented timing advantage in both discretionary and automated trading.
In other words: this indicator lets you trade ahead of time.
🔮 FORECAST ENGINE — POWERED BY LINEAR REGRESSION
At its core, the MACD Forecast integrates Linear Regression (ta.linreg) to project the MACD’s future behavior with exceptional accuracy.
Projection Modes:
• Flat Projection: Assumes trend continuity at the current level.
• LinReg Projection: Applies linear regression across N periods to mathematically forecast momentum shifts.
This dual system offers both a conservative and adaptive view of market direction.
📐 ACCURACY WITH FULL CUSTOMIZATION
Just like the MACD Full, this new version comes with 20 customizable buy-entry conditions and 20 sell-entry conditions — now enhanced with forecast-based rules that anticipate crossovers and trend reversals.
You’re not just reacting — you’re strategizing ahead of time.
⯁ HOW TO USE MACD FORECAST❓
The MACD Forecast is built on the same foundation as the classic MACD, but with predictive capabilities.
Step 1 — Spot Predicted Crossovers:
Watch for forecasted bullish or bearish crossovers. These signals anticipate when the MACD line will cross the signal line in the future, letting you prepare trades before the move.
Step 2 — Confirm with Histogram Projection:
Use the projected histogram to validate momentum direction. A rising histogram signals strengthening bullish momentum, while a falling projection points to weakening or bearish conditions.
Step 3 — Combine with Multi-Timeframe Analysis:
Use forecasts across multiple timeframes to confirm signal strength (e.g., a 1h forecast aligned with a 4h forecast).
Step 4 — Set Entry Conditions & Automation:
Customize your buy/sell rules with the 20 forecast-based conditions and enable automation for bots or alerts.
Step 5 — Trade Ahead of the Market:
By preparing for future momentum shifts instead of reacting to the past, you’ll always stay one step ahead of lagging traders.
🤖 BUILT FOR AUTOMATION AND BOTS 🤖
Whether for manual trading, quantitative strategies, or advanced algorithms, the MACD Forecast was designed to integrate seamlessly with automated systems.
With predictive logic at its core, your strategies can finally react to what’s coming, not just what already happened.
🥇 WHY THIS INDICATOR IS UNIQUE 🥇
• World’s first MACD with Linear Regression Forecasting
• Predictive Crossovers (before they appear on the chart)
• Maximum flexibility with Long & Short combinations — 20+ fully configurable conditions for tailor-made strategies
• Fully automatable for quantitative systems and advanced bots
This isn’t just an update.
It’s the final evolution of the MACD.
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🔹 CONDITIONS TO BUY 📈
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• Signal Validity: The signal will remain valid for X bars .
• Signal Sequence: Configurable as AND or OR .
🔹 MACD > Signal Smoothing
🔹 MACD < Signal Smoothing
🔹 Histogram > 0
🔹 Histogram < 0
🔹 Histogram Positive
🔹 Histogram Negative
🔹 MACD > 0
🔹 MACD < 0
🔹 Signal > 0
🔹 Signal < 0
🔹 MACD > Histogram
🔹 MACD < Histogram
🔹 Signal > Histogram
🔹 Signal < Histogram
🔹 MACD (Crossover) Signal
🔹 MACD (Crossunder) Signal
🔹 MACD (Crossover) 0
🔹 MACD (Crossunder) 0
🔹 Signal (Crossover) 0
🔹 Signal (Crossunder) 0
🔮 MACD (Crossover) Signal Forecast
🔮 MACD (Crossunder) Signal Forecast
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🔸 CONDITIONS TO SELL 📉
______________________________________________________
• Signal Validity: The signal will remain valid for X bars .
• Signal Sequence: Configurable as AND or OR .
🔸 MACD > Signal Smoothing
🔸 MACD < Signal Smoothing
🔸 Histogram > 0
🔸 Histogram < 0
🔸 Histogram Positive
🔸 Histogram Negative
🔸 MACD > 0
🔸 MACD < 0
🔸 Signal > 0
🔸 Signal < 0
🔸 MACD > Histogram
🔸 MACD < Histogram
🔸 Signal > Histogram
🔸 Signal < Histogram
🔸 MACD (Crossover) Signal
🔸 MACD (Crossunder) Signal
🔸 MACD (Crossover) 0
🔸 MACD (Crossunder) 0
🔸 Signal (Crossover) 0
🔸 Signal (Crossunder) 0
🔮 MACD (Crossover) Signal Forecast
🔮 MACD (Crossunder) Signal Forecast
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🔮 Linear Regression Function 🔮
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• Our indicator includes MACD forecasts powered by linear regression.
Forecast Types:
• Flat: Assumes prices will stay the same.
• Linreg: Makes a 'Linear Regression' forecast for n periods.
Technical Information:
• Function: ta.linreg()
Parameters:
• source: Source price series.
• length: Number of bars (period).
• offset : Offset.
• return: Linear regression curve.
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⯁ UNIQUE FEATURES
______________________________________________________
Linear Regression: (Forecast)
Signal Validity: The signal will remain valid for X bars
Signal Sequence: Configurable as AND/OR
Table of Conditions: BUY/SELL
Conditions Label: BUY/SELL
Plot Labels in the graph above: BUY/SELL
Automate & Monitor Signals/Alerts: BUY/SELL
Linear Regression (Forecast)
Signal Validity: The signal will remain valid for X bars
Signal Sequence: Configurable as AND/OR
Table of Conditions: BUY/SELL
Conditions Label: BUY/SELL
Plot Labels in the graph above: BUY/SELL
Automate & Monitor Signals/Alerts: BUY/SELL
______________________________________________________
📜 SCRIPT : MACD Forecast
🎴 Art by : @Titans_Invest & @DiFlip
👨💻 Dev by : @Titans_Invest & @DiFlip
🎑 Titans Invest — The Wizards Without Gloves 🧤
✨ Enjoy!
______________________________________________________
o Mission 🗺
• Inspire Traders to manifest Magic in the Market.
o Vision 𐓏
• To elevate collective Energy 𐓷𐓏
🎗️ In memory of João Guilherme — your light will live on forever.
RSI MOVWe can consider the 200 RSI and 200 m/s crossovers as reaction movements.
The periods I use are:
5-minute and 15-minute for short trades
1-hour and 4-hour for swing trades
Trades that can be taken with the intersection and breakout of the red moving average with the green moving average
JORGE v1 Calls Puts On CandleA multi-timeframe script built for SPX 500 options traders.
• 1m entries, 5m bias, 15m levels
• CALL signals in bright green, PUT signals in bright red
• Black arrows mark each trade idea directly on the candles
• Includes VWAP bands, EMA cloud bias, opening range, ATR targets/stops, and previous day levels
• Risk mapping with TP/SL zones based on ATR multiples
• Alerts ready for CALL, PUT, and Opening Range Breakouts
This script is designed to simplify intraday decision making, giving you fast visual signals plus context levels for discipline and consistency.
Enjoy trading! 🚀📉📈
VOLUME Full [Titans_Invest]VOLUME Full
Designed for traders who want to take volume analysis to the next level.
This version delivers deeper insight into volume activity, integrating multiple customizable filters to highlight key buying and selling pressure. It's a comprehensive solution for volume-based decision-making.
⯁ WHAT IS THE VOLUME❓
The Volume indicator is a fundamental technical analysis tool that measures the number of shares or contracts traded in a security or market during a given period. It helps traders and investors understand the strength or weakness of a price movement, confirm trends, and predict potential reversals. Volume is typically displayed as a histogram below a price chart, with each bar representing the volume traded during a specific time interval.
⯁ HOW TO USE THE VOLUME❓
The Volume indicator can be used in several ways to enhance trading decisions:
• Trend Confirmation: High volume during a price move confirms the strength of that trend, while low volume can indicate a weak or unsustainable trend.
• Breakouts: A price breakout from a pattern or range accompanied by high volume is more likely to be valid and sustainable.
• Divergence: When the price moves in one direction and volume moves in the opposite direction, it can signal a potential reversal.
• Overbought/Oversold Conditions: Extreme volume levels can sometimes indicate that an asset is overbought or oversold, though this is less straightforward than with oscillators like the RSI.
⯁ ENTRY CONDITIONS
The conditions below are fully flexible and allow for complete customization of the signal.
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🔹 CONDITIONS TO BUY 📈
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▪︎ Signal Validity: The signal will remain valid for X bars .
▪︎ Signal Sequence: Configurable as AND or OR .
🔹 volume Positive
🔹 volume Negative
🔹 volume > volume
🔹 volume < volume
🔹 volume > volume_MA
🔹 volume > volume_MA * Trigger Signal (close > open)
🔹 volume > volume_MA * Trigger Signal (Keep State P)
🔹 volume > volume_MA * Trigger Signal (close < open)
🔹 volume > volume_MA * Trigger Signal (Keep State N)
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🔸 CONDITIONS TO SELL 📉
______________________________________________________
▪︎ Signal Validity: The signal will remain valid for X bars .
▪︎ Signal Sequence: Configurable as AND or OR .
🔸 volume Positive
🔸 volume Negative
🔸 volume > volume
🔸 volume < volume
🔸 volume > volume_MA
🔸 volume > volume_MA * Trigger Signal (close > open)
🔸 volume > volume_MA * Trigger Signal (Keep State P)
🔸 volume > volume_MA * Trigger Signal (close < open)
🔸 volume > volume_MA * Trigger Signal (Keep State N)
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🤖 AUTOMATION 🤖
• You can automate the BUY and SELL signals of this indicator.
______________________________________________________
______________________________________________________
⯁ UNIQUE FEATURES
______________________________________________________
Signal Validity: The signal will remain valid for X bars
Signal Sequence: Configurable as AND/OR
Condition Table: BUY/SELL
Condition Labels: BUY/SELL
Plot Labels in the Graph Above: BUY/SELL
Displays Positive & Negative Volume.
Automate and Monitor Signals/Alerts: BUY/SELL
Signal Validity: The signal will remain valid for X bars
Signal Sequence: Configurable as AND/OR
Table of Conditions: BUY/SELL
Conditions Label: BUY/SELL
Plot Labels in the graph above: BUY/SELL
Displays Positive & Negative Volume.
Automate & Monitor Signals/Alerts: BUY/SELL
______________________________________________________
📜 SCRIPT : VOLUME Full
🎴 Art by : @Titans_Invest & @DiFlip
👨💻 Dev by : @Titans_Invest & @DiFlip
🎑 Titans Invest — The Wizards Without Gloves 🧤
✨ Enjoy!
______________________________________________________
o Mission 🗺
• Inspire Traders to manifest Magic in the Market.
o Vision 𐓏
• To elevate collective Energy 𐓷𐓏
Smart Money LITE — Daily Sweep → HQ Signals (VWAP • FVG • CHoCH) 🔗 PRO VERSION (VWAP + FVG + CHoCH — full confirmations, all timeframes):
chartedgepro.gumroad.com/l/rmnbhw
Daily liquidity sweep → confluence signals with VWAP, FVG & CHoCH. Works on all timeframes & markets (Indices, Forex, Crypto).
WHAT IT DOES
Smart Money LITE+ highlights high-quality LONG/SHORT signals only after daily liquidity is swept (previous day high/low) with confluence from VWAP, FVG and structure (BOS/CHoCH).
Works on all timeframes and across markets: indices, forex, crypto.
KEY FEATURES (Lite)
• Daily sweep logic (PDH/PDL) + previous day zones
• VWAP + deviation bands (optional) and proximity filter
• 3-bar FVG boxes (visual) with adjustable extension
• ATR/volatility filter, optional HTF trend filter
• Anti-spam cooldown, clean LONG/SHORT labels
• Alerts: HQ LONG / HQ SHORT
HOW TO USE
1. Wait for price to sweep PDH/PDL → indicator opens “signal window”.
2. Look for confluence: VWAP touch/proximity + CHoCH or BOS in direction.
3. Enter with proper risk management (stop beyond swing/zone, partials).
SETTINGS TIPS
• Enable “Require VWAP Confluence?” for strictest setups.
• Use “HTF Trend Filter?” to align with higher-timeframe EMA trend.
• Adjust “After sweep (bars)” to define signal validity window.
• FVGs are visual in Lite — advanced filtering and confirmation are in Pro.
WHO IT'S FOR
Scalpers, intraday, and swing traders looking for objective, visual signals based on liquidity sweeps and VWAP/FVG confluence.
PRO VERSION (full confirmations)
Adds advanced FVG/iFVG logic, more confluence filters, dynamic risk tools and extended alert packages — optimized for all timeframes.
👉 chartedgepro.gumroad.com/l/rmnbhw
NOTES
• For educational purposes only. No financial advice.
• “Lite” is open-source; redistribution of code follows TradingView rules.
Composite Sentiment Extremes OscillatorComposite Sentiment Extremes Oscillator (CSEO)
Created by MonkeyPhone
The Composite Sentiment Extremes Oscillator (CSEO) is a sophisticated market sentiment indicator designed to identify optimal entry and exit points by leveraging a composite of six key market data points. I developed this indicator to pinpoint moments where the risk-to-reward ratio for entering or exiting trades reaches its peak, helping traders capitalize on potential reversals. The oscillator aggregates data from the CBOE Volatility Index (VIX), CBOE Equity Put/Call Ratio (PCCE), NYSE TRIN, Net New 52-Week Highs/Lows, ICE BofA US High Yield Bond Spread (BAMLH0A0HYM2), and the percentage of S&P 500 stocks above their 200-day moving average (S5TH). Each component is normalized using a 252-bar percentrank to reflect greed (high values) or fear (low values), creating a unified 0-100 sentiment score.
The oscillator's line color reflects market conditions: red when above 60 (indicating a trending up market), gray between 40 and 60 (suggesting chop or consolidation), and green below 40 (indicating a trending down market). Notably, the higher or lower the line moves toward the extremes (88 for greed, 12 for fear), the more likely a pullback or retracement becomes, offering strategic opportunities for reversals. Given the long-term upward trend in legacy markets over decades, long signals (buy at extreme fear) tend to carry more weight than short signals (sell at extreme greed), though this dynamic may shift if markets experience a significant rollover.
This indicator performs best on the weekly timeframe, where its accuracy in identifying sentiment extremes shines, making it ideal for swing or position trading. It supports any timeframe daily or above, but lower timeframes (e.g., daily) may produce increased false signals due to data resolution limitations. Alerts can be configured for both long and short entries, allowing traders to receive notifications when the oscillator crosses the 12 (buy) or 88 (sell) thresholds—accessible via the TradingView alert interface for customized monitoring.
Use this tool to enhance your market timing, but always combine it with other analysis for confirmation. Feedback and suggestions are welcome as I continue to refine this indicator!
[ayana] TFPS - TradFi Pressure ScoreTFPS - TradFi Pressure Score: Your Market Pressure Barometer
Understand what moves Wall Street, before it moves Crypto.
This indicator is your real-time barometer for the influence of traditional financial markets (TradFi) on Crypto. It measures the combined pressure from four key quadrants—Risk Appetite (S&P 500), Market Stress (VIX), Liquidity (DXY), and Macro Expectations (US10Y)—to answer one question: "Do I have a tailwind or a headwind from the global markets?"
How to Read Your "Cockpit" in 60 Seconds
The Main Line (Overall Market Pressure)
GREEN / ABOVE 0: Bullish Tailwind. The macro environment is supportive for Crypto.
RED / BELOW 0: Bearish Headwind. The macro environment is creating pressure on Crypto.
BRIGHT Color: Pressure is ACCELERATING.
DARK Color: Pressure is DECELERATING (losing momentum).
The Dashboard (Your Command Center)
Lead/Lag Analysis: The game-changer. Tells you if TradFi is currently leading the price or vice-versa. This is your key to knowing whether to watch macro news or focus on crypto-specifics.
TradFi Influence (R²): Shows you HOW RELEVANT the macro pressure is right now. High R² means Wall Street's influence is dominant. Low R² means crypto is moving on its own narrative.
Dynamic Weights: Reveals the market's primary NARRATIVE. Is the pressure coming from Fear (VIX), Liquidity (DXY), or general Risk Appetite (SPX)?
Extreme Signals (Reversal Zones)
Stress Cloud (Z-Score): Large, opaque bars warn of statistically EXTREME greed or fear levels.
Extreme Dots: Pinpoint the moments when pressure has likely reached an unsustainable peak, often preceding turning points.
Key Strategies & Use Cases
As a Trend Filter: Simply avoid fighting the color. Don't force long trades when the TFPS shows a strong red headwind.
For Precision Entry/Exits: Use the Extreme Dots and a decelerating color on the Main Line to time your entries in confluence with your own strategy.
For Strategic Decisions: Use the Lead/Lag and R² metrics to decide where to focus your attention and how to manage portfolio risk based on the current macro regime.
Configuration
For best results, leave the engine settings on their default (auto-adaptive) mode. The indicator's core intelligence lies in its ability to adapt to changing market dynamics automatically. You can adjust the visual theme to match your chart.
SPX Levels Adjusted to Active TickerThis indicator allows you to plot custom SPX levels directly on the ES1! (E-mini S&P 500 Futures) chart, automatically adjusting for the spread between SPX and ES1!. This is particularly useful for traders who perform technical analysis on SPX but execute trades on ES1!.
Features:
Input up to three SPX key levels to track (e.g., 5000, 4950, 4900)
The script adjusts these levels in real-time based on the current spread between SPX and ES1!
Displays the spread in the chart header for quick reference
Plots updated horizontal lines that move with the spread
Includes optional labels showing the spread periodically to reduce clutter
Supports Multiple Tickers, ES1!, SPY and SPX500USD.
Ideal for futures traders who want SPX context while trading ES1!.
PRO Investing - Quant AlphaCentauri D |XLF|PRO Investing - Quant AlphaCentauri D |XLF|
1. Summary and Core Concept
This is a quantitative backtesting strategy engineered specifically for the Financial Select Sector SPDR Fund (XLF) on the Daily (1D) timeframe. The name "AlphaCentauri" reflects its goal: to seek alpha by identifying statistically significant opportunities through rigorous time series analysis.
The strategy's core principle is to move beyond conventional technical indicators and instead analyze the underlying structure and character of price data. It is designed to methodically identify conditions that have historically preceded sustained directional trends in the financial sector.
2. The Analytical Process: How It Works
This strategy employs a multi-stage quantitative process to filter for high-probability setups. It is a "mashup" of statistical concepts applied to price action.
Structural Pattern Recognition: The engine's primary function is to analyze the historical price series of XLF to identify specific, recurring structural patterns. It examines price geometry and cyclical behavior to find formations that often act as the foundation for a new, emerging trend.
Signal Execution: A signal to enter a trade is only generated when the findings from both the structural analysis and the validation stages are in agreement. This disciplined, multi-layered approach ensures the strategy remains flat during periods of high uncertainty and only engages when its quantitative criteria are fully met.
3. How to Use This Strategy
Timeframe: This strategy has been designed, tested, and optimized exclusively for the Daily (1D) timeframe on the XLF ticker. Its logic is not intended for other timeframes or assets and may produce unreliable results if used differently.
On-Chart Signals: The strategy's operation is transparent. It plots all historical buy and sell entries, along with their corresponding exits, directly on the chart for easy performance review and analysis.
4. Risk Management: The Strategy's Foundation
This strategy is built upon a foundation of strict, non-negotiable risk management, which is reflected in its code and backtesting parameters. This design complies with TradingView's guidelines for publishing realistic and responsible strategies.
Dynamic Stop-Loss and Position Sizing: A stop-loss is dynamically calculated for each trade based on recent market volatility. The strategy then automatically adjusts the position size for that trade to target a defined risk percentage. In cases of extreme market volatility, the maximum potential loss on a single trade may approach, but is designed not to exceed, 5% of total account equity. Under normal market conditions, the risk for most trades will be below this maximum threshold.
Realistic Backtesting Parameters:
Initial Capital: The backtest defaults to an initial capital of $100,000.
Commission: A realistic fee of $5.00 per order is included to simulate broker costs.
5. Disclaimer
This strategy is an educational tool provided for informational and research purposes. It is not financial advice. All trading carries a high level of risk, and past performance is not a guarantee of future results. You are solely responsible for your own trading decisions and risk management. Always conduct your own due diligence before deploying any trading strategy in a live account.
SPX Psych Levels for /ES Futures (Fair Value)Overview
This indicator displays S&P 500 psychological levels adjusted for ES futures fair value premium. These levels act as powerful magnets for price action due to the convergence of technical trading and options market dynamics.
What is Fair Value Premium?
Simply put, its the difference between the SPX price and the ES futures price. This changes dynamically based on interest rate, dividends, and time to expiration.
Why Psych Levels are Increasingly Important
Psychological levels are round numbers where traders naturally place orders. These obvious levels attract stop losses, profit targets, and breakout orders from both retail and institutional traders. Algorithms often target these same levels, creating a self-fulfilling prophecy of support and resistance. Importantly, this effect has been exacerbated by the options market.
Using May 2025 as an example, SPX options averaged 3.46 million contracts a day ≈US $1.8 trillion notional, dwarfing trading in SPY or ES/MES futures. 0-day-to-expiry (0DTE) trades hit a record-high 61% share of all SPX volume, making the options complex the primary arena for intraday price discovery.
Strikes at psychological numbers (ending in 00 and 50) captured 66% of total open interest and 58% of 0DTE volume for the entire month. This massive concentration at round number strikes creates powerful hedging flows:
Dealer Gamma Hedging: As price approaches these levels, market makers must dynamically hedge their options exposure, creating reflexive buying/selling pressure
Pin Risk: Options dealers face maximum uncertainty at these levels near expiration, leading to increased hedging activity
Charm Flows: Time decay accelerates near these levels, forcing position adjustments
How It Works
The indicator automatically:
Calculates the fair value premium between ES futures and SPX using real-time interest rate data, dividends, and time to expiration
Adjusts SPX round numbers by this premium to show where they appear on ES charts
Updates once daily at futures session open (5PM CT) to maintain stable reference points throughout the trading session
Key Features
All TradingView Native: All calculations performed automatically using data available within TradingView - no external data feeds or manual updates required
Multiple Level Increments: Display major (100-point), intermediate (50-point), and minor (25-point) psychological levels
Margin of Error Zones: Optional ±2.5 point zones accounting for fair value calculation variance
Full Customization: Colors, line styles, and widths for each level type
Fair Value Info Table: Displays current contract, fair value calculation, interest rate, and days to expiration
Automatic Contract Detection: Works on ES1!/MES1! continuous contracts and automatically detects the current front month contract
Important Notes
This indicator does not access any options data. It identifies levels where options activity naturally concentrates based on market structure. The power comes from understanding that these obvious levels create predictable dealer hedging flows, making them high-probability reaction zones.
Trading Applications
These levels can be used as dynamic areas of interest to be incorporated into a complete trading strategy.
